no code implementations • 12 May 2021 • Dania Humaidan, Sebastian Otte, Christian Gumbsch, Charley Wu, Martin V. Butz
A critical challenge for any intelligent system is to infer structure from continuous data streams.
no code implementations • 12 May 2020 • Dania Humaidan, Sebastian Otte, Martin V. Butz
Here, we introduce a hierarchical, surprise-gated recurrent neural network architecture, which models this process and develops compact compressions of distinct event-like contexts.
2 code implementations • 19 Sep 2018 • Martin V. Butz, David Bilkey, Dania Humaidan, Alistair Knott, Sebastian Otte
We introduce REPRISE, a REtrospective and PRospective Inference SchEme, which learns temporal event-predictive models of dynamical systems.